scholarly journals Design for Nonlinear Networked Control Systems with Time Delay Governed by Markov Chain with Partly Unknown Transition Probabilities

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Yan-Feng Wang ◽  
Zu-Xin Li ◽  
Hui-Ying Chen ◽  
Li-Di Quan ◽  
Xiao-Rui Guo

The problem of state feedback control for a class of nonlinear networked control systems with time delay is discussed in this paper. The time delay is modeled as a finite state Markov chain of which transition probabilities are partly unknown. The closed-loop system model is obtained by means of state augmentation. A sufficient condition is given which guarantees the stochastic stability of the closed-loop system in the form of linear matrix inequalities and the maximum bound of the nonlinearity is also obtained. Finally, a simulation example is used to show the validity of the proposed method.

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Wang Yan-feng ◽  
Wang Pei-liang ◽  
Li Zu-xin ◽  
Chen Hui-ying

This paper is concerned with the problem of designing a fault-tolerant controller for uncertain discrete-time networked control systems against actuator possible fault. The step difference between the running stepkand the time stamp of the used plant state is modeled as a finite state Markov chain of which the transition probabilities matrix information is limited. By introducing actuator fault indicator matrix, the closed-loop system model is obtained by means of state augmentation technique. The sufficient conditions on the stochastic stability of the closed-loop system are given and the fault-tolerant controller is designed by solving a linear matrix inequality. A numerical example is presented to illustrate the effectiveness of the proposed method.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Li Qiu ◽  
Chengxiang Liu ◽  
Fengqi Yao ◽  
Gang Xu

This paper focuses on the stability issue of discrete-time networked control systems with random Markovian delays and uncertain transition probabilities, wherein the random time delays exist in the sensor-to-controller and controller-to-actuator. The resulting closed-loop system is modeled as a discrete-time Markovian delays system governed by two Markov chains. Using Lyapunov stability theory, a result is established on the Markovian structure and ensured that the closed-loop system is stochastically stable. A simulation example illustrates the validity and feasibility of the results.


2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yanfeng Wang ◽  
Peiliang Wang ◽  
Zuxin Li ◽  
Huiying Chen

This paper investigates the observer-based controller design problem for a class of nonlinear networked control systems with random time-delays. The nonlinearity is assumed to satisfy a global Lipschitz condition and two dependent Markov chains are employed to describe the time-delay from sensor to controller (S-C delay) and the time-delay from controller to actuator (C-A delay), respectively. The transition probabilities of S-C delay and C-A delay are both assumed to be partly inaccessible. Sufficient conditions on the stochastic stability for the closed-loop systems are obtained by constructing proper Lyapunov functional. The methods of calculating the controller and the observer gain matrix are also given. Two numerical examples are used to illustrate the effectiveness of the proposed method.


Author(s):  
Qian Zhang ◽  
Huaicheng Yan ◽  
Shiming Chen ◽  
Xisheng Zhan ◽  
Xiaowei Jiang

This paper is concerned with the problem of finite-time dissipative control for networked control systems by hybrid triggered scheme. In order to save network resources, a hybrid triggered scheme is proposed, which consists of time-triggered scheme and event-triggered scheme simultaneously. Firstly, sufficient conditions are derived to guarantee that the closed-loop system is finite-time bounded (FTBD) and [Formula: see text] dissipative. Secondly, the corresponding controller design approach is presented based on the derived conditions. Finally, a numerical example is presented to show the effectiveness of the proposed approach.


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